def _png_to_nximg(data, image_format):
data_nximg = bytes()
with BytesIO(data) as io_png:
with BytesIO() as io_nximg:
png = PngImageFile(io_png)
w, h = png.width, png.height
if image_format == IMAGE_FORMAT_1555:
for y in range(h):
for x in range(w):
[r, g, b, a] = png.getpixel((x, y))
IOHelper.write_struct(io_nximg, "<2B",
*NXColor.to_1555(r, g, b, a))
elif image_format == IMAGE_FORMAT_4444:
for y in range(h):
for x in range(w):
[r, g, b, a] = png.getpixel((x, y))
IOHelper.write_struct(io_nximg, "<2B",
*NXColor.to_4444(r, g, b, a))
elif image_format == IMAGE_FORMAT_8888:
for y in range(h):
for x in range(w):
[r, g, b, a] = png.getpixel((x, y))
IOHelper.write_struct(io_nximg, "<4B", b, g, r, a)
else:
raise Exception('Unsupport image format: %s' %
image_format)
data_nximg = IOHelper.read_range(io_nximg)
return data_nximg, w, h
def load_buffer(buffer_path, replay_buffer):
file_list = os.listdir(buffer_path)
for idx, file_name in enumerate(file_list[:-1]):
if idx > 2000:
print (idx)
im = PngImageFile(os.path.join(buffer_path, file_name))
im_next = PngImageFile(os.path.join(buffer_path, file_list[idx+1]))
## Change to action space, now two-dimensional
throttle, steer, brake = float(im.text['control_throttle']), float(im.text['control_steer']), float(im.text['control_brake'])
action = np.zeros((2,))
action[0] = throttle if throttle > 0.0 else (-brake)
action[1] = steer
reward = np.array([float(im.text['reward'])])
location = np.array([float(im.text['location_x']), float(im.text['location_y']), float(im.text['location_z'])])
obs = Image.open(os.path.join(buffer_path, file_name))
next_obs = Image.open(os.path.join(buffer_path, file_list[idx+1]))
path = dict()
path['observations'] = [{'image': np.array(obs).astype(np.float32) / 255.0},]
path['next_observations'] = [{'image': np.array(next_obs).astype(np.float32) / 255.0}, ]
path['actions'] = [action,]
path['rewards'] = [reward,]
path['terminals'] = [(False,),]
print ('Location: ', idx, location)
replay_buffer.add_path(path)
print ('Replay Buffer Loaded: ', replay_buffer._size)
def ex_oxygen(img):
from PIL.PngImagePlugin import PngImageFile as Png
coreimg = Png(img)
w = coreimg.getbbox()[2]
h = coreimg.getbbox()[3] // 2
chars = [coreimg.getpixel((i, h))[0] for i in range(0, w, 7)]
message = ''.join(map(chr, chars))
result = ''.join(map(lambda x: chr(int(x)), message[43:-4].split(',')))
return 7, result
def add_tags_to_png_file(fpath):
try:
info = create_file_info(fpath)
png_image = PngImageFile(open(fpath, 'rb'))
png_info = PngInfo()
for k, v in info.items():
png_info.add_text(k, v)
png_image.save(fpath, pnginfo=png_info)
except (Exception, OSError):
print("WARNING: Could not add debug info to file '{}'.".format(fpath))
traceback.print_exc()
def send_png(self, fname):
png = PngImageFile(fname)
png.load() # load metadata
with open(fname, "rb") as f:
return self.bot.send_photo(
chat_id=self.chat_id,
photo=f,
parse_mode="Markdown",
caption=png.info.get("Comment", "`{}`".format(fname.name)),
)
def get_colours_from_image(self, image: PngImageFile, country: str) -> Set[str]:
# we set the colour profile to RGBA because PIL moans about transparency with RGB
image = image.convert("RGBA")
num_pixels = reduce(mul, image.size)
img_colours = image.getcolors(num_pixels)
if not img_colours:
print(f"Could not get image colours for {country}")
return set()
# print(sorted(img_colours, key=lambda x: x[0], reverse=True))
freq_colours = [FreqColour(f, Colour(c[:3])) for f, c in img_colours]
colours = self._reduce_colours(freq_colours, num_pixels)
return colours
def savemeta(*args, **kwargs):
path = args[1]
if path.endswith(".fig"):
import pickle as pkl
pkl.dump(args[0], open(path, 'wb'))
else:
mpl_savefig(*args, **kwargs)
#fig = args[0]
if path.endswith(".png"):
targetImage = PngImageFile(path)
metadata = PngInfo()
metadata.add_text("Description", str(meta))
targetImage.save(path, pnginfo=metadata)
def load_spectrogram(cls, fname, to_nparray=True):
'''
Loads a .png spectrogram file,
and returns a numpy array
:param fname: file to load
:type fname: str
:param to_nparray: if True, convert torchvision. Image
instance to a numpy array, and return that as result
:type to_nparray: bool
:returns tuple: the image and the .png file's possibly empty metadata dict
:rtype: ({np.array|torchvision.Image}, {str : str})
:raises FileNotFoundError
'''
if not os.path.exists(fname):
raise FileNotFoundError(f"File {fname} does not exist.")
png_img = PngImageFile(fname)
try:
info = png_img.text
except Exception as e:
cls.log.info(f"No available info in .png file: {repr(e)}")
info = None
img_obj = Image.open(fname)
if to_nparray:
res = np.asarray(img_obj)
else:
res = img_obj
return (res, info)
def write_png_metadata(filename, settings):
targetImage = PngImageFile(filename)
metadata = PngInfo()
for (k, v) in settings.items():
if type(v) == list:
value = ""
for item in v:
value += str(item) + " "
v = value
if type(v) == bool:
v = str(v)
if v is None:
continue
else:
metadata.add_text(k, str(v))
targetImage.save(filename, pnginfo=metadata)
def test_custom_encode(colors):
result, meta = encode(uid_18, "custom", colors[0], colors[1], colors[2])
result.save("test.png", pnginfo=meta)
with PngImageFile("test.png") as fp:
assert decode(fp) == uid_18
delete_test_png()
def svg_image_factory(fp, filename):
mime_type = magic.from_buffer(fp.read(1024), mime=True)
if mime_type != "image/svg+xml":
raise TypeError
fp.seek(0)
png_data = PNGSurface.convert(fp.read(), url_fetcher=url_fetcher)
return PngImageFile(BytesIO(png_data))
def sample_image_path(self):
"""Copy the sample image to to a unique file name and return the path.
Returns:
tuple of (the filename, the new sample image path)
"""
filename = self.generate_alphanumeric() + ".png"
new_file = self.tmp_file_path(filename)
shutil.copy(self.original_sample_image_path, new_file)
# make the image content unique
image_file = PngImageFile(open(new_file, "r"))
info = PngInfo()
info.add_text('Comment', self.generate_alphanumeric(length=30))
image_file.save(new_file, pnginfo=info)
self.temp_files.append(new_file)
return (filename, new_file)
def get_dict_from_pnginfo(image_filename="", dict_name=""):
dict_to_return = {}
targetImage = PngImageFile(image_filename)
all_settings_dict = targetImage.text
for settings_key in all_settings_dict:
if (settings_key == dict_name):
dict_to_return = json.loads(all_settings_dict[settings_key])
return dict_to_return
def _action(uid: str, color: Color = Color.red):
result, meta = encode(uid)
result.save("test.png", pnginfo=meta)
with PngImageFile("test.png") as fp:
uid_result = decode(fp)
return result, uid_result
def __getitem__(self, index):
"""Return a data point and its metadata information.
Parameters:
index - - a random integer for data indexing
Returns a dictionary that contains A, B, A_paths and B_paths
A (tensor) - - an image in the input domain
B (tensor) - - its corresponding image in the target domain
A_paths (str) - - image paths
B_paths (str) - - image paths (same as A_paths)
"""
# read a image given a random integer index
AB_path = self.AB_paths[index]
# print(AB_path)
path = AB_path.replace('train', 'train2')
# print(index)
AB = Image.open(AB_path)
targetImage = PngImageFile(AB_path)
des = int(targetImage.text['des'])
# des = int(AB.info['des'])
# matrix = im.info['Comment']
# split AB image into A and B
w, h = AB.size
w2 = int(w / 2)
A = AB.crop((0, 0, w2, h))
B = AB.crop((w2, 0, w, h))
opacity = 50
flash = skimage.img_as_float(A)
ambient = skimage.img_as_float(B)
# im = A_float * opacity / 100 + B_float * (100 - opacity) / 100
# paper version 4: from A flash 0.5 ambient 1.7 to flash 1.7 ambient 0.5
A = flash * 1.1+ ambient * 1.1
A = xyztorgb(A,des)
# opacity2 = opacity + 0.7
# if opacity2 > 2:
# opacity2 = 2
B = flash * 2.2 + ambient * 1.1
B = xyztorgb(B,des)
# cv2.imwrite(path_AB, im_AB)
# im = (im * 255 / np.max(im)).astype('uint8')
# print(blended)
# im = (im * 255 / np.max(im)).astype('uint8')
# im = Image.fromarray(im)
# apply the same transform to both A and B
transform_params = get_params(self.opt, A.size)
A_transform = get_transform(self.opt, transform_params, grayscale=(self.input_nc == 1))
B_transform = get_transform(self.opt, transform_params, grayscale=(self.output_nc == 1))
A = A_transform(A)
B = B_transform(B)
return {'A': A, 'B': B, 'A_paths': AB_path, 'B_paths': AB_path}
def replace_meta(filename, fields):
metaname = get_dumpfile(filename)
with open(metaname) as json_file:
meta = json.load(json_file)
if fields and fields[0] != '*':
print(f"overwriting metadata[{fields}] in {filename} from {metaname}")
newmeta = {}
for f in fields:
newmeta[f] = meta[f]
else:
print(f"overwriting metadata in {filename} from {metaname}")
newmeta = meta
newmeta['Metadata Modification Time'] = f"{datetime.now()}"
img = PngImageFile(filename)
metadata = PngInfo()
for f in newmeta:
metadata.add_text(f, newmeta[f])
img.save(filename, pnginfo=metadata)
def setUp(self):
self.mock_button_repository = AbstractButtonRepository(None)
self.directory = os.path.dirname(os.path.abspath(__file__))
self.new_tab_template = PngImageFile(
os.path.join(self.directory,
'data/buttons/chrome/new_tab_template_chrome.png'))
self.new_tab_template = convert_picture_to_grayscale(
self.new_tab_template)
self.new_tab_template = convert_picture_to_numpy_array(
self.new_tab_template)
self.new_win_template = PngImageFile(
os.path.join(
self.directory,
'data/buttons/chrome/new_windows_template_chrome.png'))
self.new_win_template = convert_picture_to_grayscale(
self.new_win_template)
self.new_win_template = convert_picture_to_numpy_array(
self.new_win_template)
def __binarizing(self, img: PngImageFile, threshold):
pixdata = img.load()
w, h = img.size
for y in range(h):
for x in range(w):
if pixdata[x, y] < threshold:
pixdata[x, y] = 0
else:
pixdata[x, y] = 255
return img
def decode_from_img(self, file: BytesIO) -> str:
"""Decodes secrets from png squares
Parameters
___________
file: bytes
file object produced by opening in 'rb' mode or other means"""
img = PngImageFile(fp=file)
try:
edge = img.text["edge"]
except KeyError: # img was not upscaled
pass
else: # img was upscaled so we scale it down as prescribed by metadata
edge = int(edge)
img = img.resize((edge, edge), resample=Image.NEAREST)
# asarray creates readonly hence the np.array
return self.decode(np.array(img))
def load_buffer(buffer_path, replay_buffer):
file_list = os.listdir(buffer_path)
for idx, file_name in enumerate(file_list[:-1]):
if idx % 1000 == 0:
print(idx)
im = PngImageFile(os.path.join(buffer_path, file_name))
im_next = PngImageFile(os.path.join(buffer_path, file_list[idx + 1]))
action = np.array([
float(im.text['control_throttle']),
float(im.text['control_steer']),
float(im.text['control_brake'])
])
reward = np.array([float(im.text['reward'])])
obs = Image.open(os.path.join(buffer_path, file_name))
next_obs = Image.open(os.path.join(buffer_path, file_list[idx + 1]))
# Since we are using obs_dict replay buffer, we can only
# call add_sample
path = dict()
path['observations'] = [
{
'image': np.array(obs).astype(np.float32) / 255.0
},
]
path['next_observations'] = [
{
'image': np.array(next_obs).astype(np.float32) / 255.0
},
]
path['actions'] = [
action,
]
path['rewards'] = [
reward,
]
path['terminals'] = [
(False, ),
]
replay_buffer.add_path(path)
print('Replay Buffer Loaded: ', replay_buffer._size)
def indexes_from_image(image: PngImageFile, sprite_idx: int) -> list:
assert (0 <= sprite_idx <= 255)
sprite_x = (sprite_idx % 16) * 8
sprite_y = (sprite_idx // 16) * 8
assert (0 <= sprite_x <= (128 - 8))
assert (0 <= sprite_y <= (128 - 8))
ret = [0 for _ in range(0, 64)]
for y in range(0, 8):
for x in range(0, 8):
ret[y * 8 + x] = image.getpixel((x + sprite_x, y + sprite_y))
assert (len(ret) == 64)
return ret
def cli_decode(path: str, color: str = "red"):
"""Decode a snowflake image at the given file PATH"""
try:
set_color = Color[color]
except KeyError:
raise ColorError("Invalid color passed.")
try:
with PngImageFile(path) as fp:
print(decode(fp, set_color))
except Exception as e:
logging.error(f"Error: {e}")
def on_save_clicked(self, button):
current_path = self.entry.get_text()
# write metadata
metadata = PngInfo()
metadata.add_text("screenshat", self.entryy.get_text())
img = PngImageFile(img_path)
img.save(img_path, pnginfo=metadata)
# Update config file
pathlib.Path(config_path).write_text(current_path)
# in doubt do mkdir -p new directory
pathlib.Path(current_path).mkdir(parents=True, exist_ok=True)
# move file
shutil.move(img_path, current_path)
self.destroy()
def test_no_metadata(caplog):
caplog.set_level(logging.WARNING)
with PngImageFile("src/tests/no_meta.png") as fp:
decode(fp)
assert (
"Warning: Unable to fetch image metadata, using default value (Red).\n"
in caplog.text)
result = decode(fp, Color.orange)
assert result == uid_18
def encrypt_png(self, in_path: PathType, out_path: PathType) -> None:
image = PngImageFile(in_path)
# convert pixels to bytes in order to encrypt them
im_bytes = bytearray(self.__get_pixels(image))
# get random IV and calculate MAC
iv = get_random_bytes(CryptoAES.block_size)
h = HMAC.new(self.__key, digestmod=SHA256)
h.update(im_bytes)
# create metadata object in order to save IV and MAC to image
metadata = PngInfo()
metadata.add_text('iv', iv.hex())
metadata.add_text('mac', h.hexdigest())
print(f'writing IV = {iv.hex()} and MAC = {h.hexdigest()} to image metadata')
# encrypt image
cipher = CryptoAES.new(self.__key, CryptoAES.MODE_ECB)
enc_data = cipher.encrypt(im_bytes)
# write image to file with metadata
image.frombytes(enc_data)
image.save(out_path, pnginfo=metadata)
def optimize_png(img: PngImageFile,
tmp_file: Any,
quality: int = 95) -> PngImageFile:
output_path = "/tmp/" + str(uuid.uuid4())
if quality >= 100:
return img
if quality % 10 == 0:
speed = int(quality /
10) # quality is inversely related to pngquant speed
else:
# each interval of 10 is related to one speed:
# [90 - 99] --> speed 9
speed = int(floor((quality - (quality % 10)) / 10))
command = [
PNGQUANT_PATH,
"--strip",
"--force",
"--output",
output_path,
"-s" + str(speed),
tmp_file.name,
]
try:
img.save(tmp_file.name, format=img.format)
subprocess.check_output(command, stderr=subprocess.STDOUT)
img = Image.open(output_path)
if Path(output_path).exists():
Path(output_path).unlink()
except (OSError, subprocess.CalledProcessError) as error:
raise ITSTransformError("ITSTransform Error: " + str(error))
return img
def paint_bolnur_katskhuri_cross():
"""Save an image of a Bolnur-Kathskuri cross, as seen on the flag of Georgia"""
# Make the rounded bar with transparent background available
rounded_bar_file = paint_rounded_bar()
# Open the rounded bars as images
rounded_bar_horizontal = PainterUtils.read_flag_drawing(rounded_bar_file)
rounded_bar_vertical = PainterUtils.read_flag_drawing(rounded_bar_file)
# In principle, it is not necessary to import PngImageFile explicitly, and call rotate with the
# class explicitly and an instance as first parameter, but when you do so, you can navigate
# more easily to the source code of the rotate function.
rounded_bar_vertical = PngImageFile.rotate(rounded_bar_vertical, angle=90,
resample=Image.BICUBIC, expand=True)
# When rotating, the size can change up to 1 pixel. E.g. a bar of (2757, 995) has size
# (996, 2757) after rotation with expand=True, regardless of resample parameter. To
# counteract this, we define the size of the vertical bar to exact the same size as the
# size of the horizontal bar, but width and height interchanged.
rounded_bar_vertical = rounded_bar_vertical.resize(
size=(rounded_bar_horizontal.size[1], rounded_bar_horizontal.size[0]),
resample=Image.NEAREST)
# Create the canvas
W = rounded_bar_horizontal.size[0]
H = rounded_bar_vertical.size[1]
cross = Image.new("RGBA", (W, H), (255, 255, 255, 0))
# Determine where to position the bars
D = rounded_bar_horizontal.size[1]
left = int(round(W / 2 - D / 2))
upper = int(round(H / 2 - D / 2))
right = int(round(W / 2 + D / 2))
lower = int(round(H / 2 + D / 2))
if False: # Set to true for debug mode
print('W:{W}, H:{H}, D:{D}, left:{left}, upper:{upper}, '
'right:{right}, lower:{lower}, width: {width}, height: {height}'.
format(W=W, H=H, D=D, left=left, upper=upper,
right=right, lower=lower, width=right - left, height=lower - upper))
# Paste the bars
cross.paste(im=rounded_bar_horizontal, box=(0, upper, W, lower), mask=rounded_bar_horizontal)
cross.paste(im=rounded_bar_vertical, box=(left, 0, right, H), mask=rounded_bar_vertical)
# cross.paste(im=rounded_bar_horizontal, box=(0, upper, W, lower), mask=None)
# cross.paste(im=rounded_bar_vertical, box=(left, 0, right, H), mask=None)
# Save the image
PainterUtils.write_flag_drawing(cross, 'bolnur_katskhuri_cross')
def process(self, image: PngImageFile) -> Image.Image:
width, height = image.width, image.height
current_aspect = width / height
# Crop the image to a 16:9 aspect ratio
if current_aspect > self.aspect:
# Crop the left and right edges
new_width = int(self.aspect * height)
offset = (width - new_width) / 2
resize = (offset, 0, width - offset, height)
else:
# Crop the top and bottom
new_height = int(width / self.aspect)
offset = (height - new_height) / 2
resize = (0, offset, width, height - offset)
return image.crop(resize)
def load_undistorted_segmentation(self, image: str) -> np.ndarray:
"""Load an undistorted image segmentation."""
segmentation_file = self._undistorted_segmentation_file(image)
with self.io_handler.open(segmentation_file, "rb") as fp:
with PngImageFile(fp) as png_image:
# TODO: We do not write a header tag in the metadata. Might be good safety check.
data = np.array(png_image)
if data.ndim == 2:
return data
elif data.ndim == 3:
return data[:, :, 0]
# TODO we can optionally return also the instances and scores:
# instances = (
# data[:, :, 1].astype(np.int16) + data[:, :, 2].astype(np.int16) * 256
# )
# scores = data[:, :, 3].astype(np.float32) / 256.0
else:
raise IndexError
def restore_instrument_settings(filename="", instrument_dict=[]):
isimage = False
if (filename.endswith('PNG') or filename.endswith('png')):
targetImage = PngImageFile(filename)
all_settings_dict = targetImage.text
else:
infile = open('filename', )
all_settings_dict = json.load(infile)
rm = pyvisa.ResourceManager()
supported_inst_dict = {
'k2308_unique_scpi': "KEITHLEY INSTRUMENTS INC.,MODEL 2308",
'k2460_unique_scpi': "KEITHLEY INSTRUMENTS,MODEL 2460",
'hmp4040_unique_scpi': "HAMEG,HMP4040",
'tek_afg3000_unique_scpi': "TEKTRONIX,AFG3102",
'plz4w_unique_scpi': "KIKUSUI,PLZ164WA,",
'key_33250a_unique_scpi': "Agilent Technologies,33250A"
}
for settings_key in all_settings_dict: # loop thru all settings inside image
if (settings_key
in supported_inst_dict): # only process supported instruments
if (isimage):
unique_scpi = json.loads(
all_settings_dict[settings_key]) # json method needed
else:
unique_scpi = all_settings_dict[
settings_key] # json method not needed
for instrument_key in instrument_dict: # loop thru all connected instruments
if (
instrument_key.startswith(
supported_inst_dict[settings_key])
): # only process connected instruments that match supported instruments
instrument = rm.open_resource(
instrument_dict[instrument_key])
instrument.write('*RST')
time.sleep(2)
for scpi_cmd in unique_scpi:
instrument.write(scpi_cmd)
def decrypt_png(self, in_path: PathType, out_path: PathType) -> None:
image = PngImageFile(in_path)
iv: Optional[str] = None
mac: Optional[str] = None
# try to get IV from metadata
try:
iv = image.text['iv']
print(f'found IV = {iv}')
except KeyError:
print('IV was not found in file')
# try to get MAC from metadata
try:
mac = image.text['mac']
print(f'found MAC = {mac}')
except KeyError:
print('MAC was not found in file')
# convert pixels to bytes in order to decrypt them
im_bytes = bytearray(self.__get_pixels(image))
# decrypt image
cipher = CryptoAES.new(self.__key, CryptoAES.MODE_ECB)
dec: bytes = cipher.decrypt(im_bytes)
# try to verify MAC
try:
self.__hmac.update(dec)
self.__hmac.verify(bytes.fromhex(mac))
print('MAC is valid')
except ValueError:
print('MAC is invalid')
# don't forget about metadata
metadata = PngInfo()
metadata.add_text('iv', iv)
metadata.add_text('mac', mac)
# save decrypted image to file
image.frombytes(dec)
image.save(out_path, pnginfo=metadata)
def _get_EXIF_DateTimeOriginal(self, file_path):
""" try to get the recording date from the EXIF in PNG file """
try:
image = PngImageFile(file_path)
metadata = PngInfo()
exif_array = []
for i in image.text:
compile = i, str(image.text[i])
exif_array.append(compile)
if len(exif_array) > 0:
header = exif_array[0][0]
if header.startswith("XML"):
xml = exif_array[0][1]
for line in xml.splitlines():
if 'DateCreated' in line:
idx1 = line.find('>')
idx2 = line.rfind('<')
if (idx1 != -1) and (idx2 != -1):
dt = line[idx1 + 1:idx2]
return dt
except Exception as err:
pass # returns None
return None
